Sound transmitting and receiving equipment, such as sonar, is used in an underwater environment to detect sound reflective objects that are on the surface or below the surface of the water. Sonar systems can be broadly divided into two types: active sonar and passive sonar. An underwater sound source, such as active sonar, includes a transmitter that emits a sound wave that can be reflected off of a sound reflective object and a receiver that detects and measures the time of reception of the reflected sound wave. The distance to a sound reflective object can be determined by measuring the time difference from the transmission of the sound wave to reception of reflected sound wave. A sonar receiver is typically co-located with the active sonar transmitter, but a receiver may also be at a different physical location. A passive sonar system includes an underwater sound receiver that operates covertly but can only detect objects emitting sounds louder than the ambient noise of the environment. For a sonar receiver to detect sounds propagating from a target, the strength of the sound must be larger the variables represented in the sonar equation. The sonar equation for a passive sonar detection of a sound source can be expressed as:SE=SL−TL+DI−AN−DT 
Where:
SE=Signal Excess. (This value must be positive for detection to occur)
SL=Source Level
TL=Transmission Loss
DI=Directivity Index
AN=Ambient Noise (background)
DT=Detection Threshold
All of the sonar equation inputs are expressed in decibels (dB).
Similarly, the sonar equation for an active sonar detection of a sound reflective object can be expressed as:SE=SL−2TL+TS+DI−AN−DT Where:                SE=Signal Excess. (This value must be positive for detection to occur)        TS=Target Strength (The strength of the sound signal returning to the sonar receiver, target strength is aspect dependent and is typically defined as        
            reflected      ⁢                          ⁢      energy              incident      ⁢                          ⁢      energy        ⁢            )        .                  SL=Source Level. (The strength of the signal transmitted by an active sonar).        2TL=Transmission Loss (This accounts for losses in both directions).        DI=Directivity Index        AN=Ambient Noise (background)        DT=Detection ThresholdIn some applications, the active sonar equation may also include reverberation (RL), which is subtracted from the source level.        
To ascertain the performance of underwater sound transmitting and receiving equipment, the equipment is usually tested in a controlled environment, such as an underwater test range. In an ideal isotropic environment, a sound wave will propagate spherically outward in a straight line from a point source. However, the ocean environment is not isotropic, so sound waves emitted from a sound source do not propagate through the water in a linear fashion due to differences in temperature and pressure in the underwater environment. The temperature of the water comprising a body of water, such as an underwater test range, varies with depth and frequently between depths of 30 and 100 meters there are often marked changes, called layers, which divide the warmer surface water from the remaining colder, deeper waters. Under these temperature and pressure conditions, a sound wave bends, or refracts, off each layer as the sound wave passes through the water along its propagation path. The refraction or bending of the sound waves may cause detection “blind spots” where detection of a sound reflective object is precluded because the sound waves emitted from the sound source are unable to reach a specific area or sound waves reflecting off of a sound reflective object are unable to return to the sound source receiver location.
Further, the surrounding acoustic environment also affects sound propagation and the detectability of sound traveling through the water. Some of the acoustic environment variables that affect the propagation and detectability of sound in water include the agitation of the sea surface, ambient noise, transmission losses, reverberation, scattering, and attenuation, for example. The surrounding acoustic environment variables typically attenuate the power of a sound wave originating from the sound source and mask any active sonar returning sound waves, making detection of the sound reflective object difficult. Before a sound source, such as sonar, can be tested objectively, the acoustic conditions likely to be encountered must be measured and its potential impact on the scheduled test events must be understood.
The variability of the acoustic environment in a controlled environment, such as an underwater test range, results in uncertainties in the expected acoustic sound propagation paths, which may adversely impact the validity of test events designed to objectively test the ability of an underwater sound transmitting and receiving system under test to detect a sound reflective target object.
To understand the impact of the acoustic conditions on sound transmitting and receiving equipment performance, complex mathematical equations, or algorithms, were developed to model acoustic conditions and many of the environmental variables. The Hamilton model, Wenz model, Helmholtz wave equations and sonar equations are mathematical equations that classically describe the ocean environment, ocean bottom characterization, and ocean ambient noise. Existing models, including Ray Models, Parabolic Equation Models, Normal Mode Models and Coupled Mode Models, assume similar boundary conditions and acoustic frequencies, and their solutions are typically approximations of the Helmholtz equation. For example, U.S. Pat. No. 7,002,877 discloses a method for predicting sonar performance in littoral waters by modeling acoustic reverberation. Each of these models is subject to and limited by computational errors associated with the complex mathematical algorithms used and the speed of response is limited by the processing capabilities of the computer used for computational processing.
Very complex programs also exist for making predictions for active and passive sonar performance based on the acoustic environment, such as mission planning tools. These complex models require the input of acoustic environmental data including depth, sound speed, propagation and absorption losses and ambient noise, as well as target strength, directivity index, and system equipment detection characteristics. These models are expensive to construct, maintain and typically use only historical sound velocity profile (SVP) data, which includes depth and sound speed data, for an area, which may not be representative of the conditions encountered during testing. For example, PC-IMAT 5.0, which uses the MPP ray trace model, requires the input of several acoustic environment variables before a sound ray trace can be output for a specified angle at a specific depth. PC-IMAT 5.0, which is used by the U.S. Navy for sonar performance mission planning, models the entire acoustic environment and provides specific ranges, depth, and even emission wave form recommendations, includes embedded historical SVP data that is used to generate these specific recommendations for a particular area. The SVP data for a particular area, such as a test range, may vary significantly during the course of a day or test event. Further, due to the large number of input variables and program complexity of these modeling programs, the computational processing required is extensive and the response time is slow.
Modeling programs that account for all of the acoustic environment variables that affect the propagation of sound in water may be necessary for real-world submarine detection and tracking operations, but these modeling programs are overly complex, requiring the input of too many data variables and have too slow a response time to support a test team in the development, test, and evaluation of the detection potential of underwater sound transmitting and receiving equipment, such as sonar systems. More specifically, there is no existing model that quickly models sound propagation in a current acoustic environment enabling a test team to assess the impact of the current acoustic conditions on scheduled test events.
What is needed is a quick and simple system and method for a test team to be able to model sound propagation paths for a sound source in the current acoustic environment of a test area. More specifically, what is needed is a modeling capability for an underwater test environment that will output a graphic representation, or plot, of the existing sound propagation paths for a sound source quickly using a minimum number of acoustic environment input variables to enable a test team to understand the impact of the current acoustic conditions on scheduled test events.